为何我的if-elif-else语句输出全为相同值？求排查解决

我需要对.csv文件中的testResp.keys_raw、location和money列进行多条件判断，为每个受试者的所有单词设置word_value_dict[word]的值：1代表正确，-1代表错误。但目前所有输出结果均为-1，不符合预期。

现有代码如下：

# get correct/incorrect for each word from testTrials.csv
word_value_dict = {}
try:
    df = pd.read_csv(s + 'testTrials.csv')
    with open(s + 'testTrials.csv') as testTrials_file:
        for row_index, row in df.iterrows():
            if pd.isna( row['money'] ) or row['money'] == 'money':
                continue
            word = row['word']
            money = float( row['money'] )
            ISI = float( row['ISI'] )
            response = row['testResp.keys_raw']
            location = float( row['location'])
            print(f"{s} : Row {row_index}: Response={response}, Location={location}, Money={money}")

            # check if the money value corresponds to a correct word
            if response == 'c' and location == -150 and money == 1:
                word_value_dict[word] = 1 #correct word
            elif response == 'a' and location == 150 and money == 1:
                word_value_dict[word] = 1 #correct word
            elif response == 'c' and location == -150 and money == 0.01:
                word_value_dict[word] = 1 #correct word 
            elif response == 'a' and location == 150 and money == 0.01:
                word_value_dict[word] = 1 #correct word
            elif response == 'c' and location == 0:
                word_value_dict[word] = -1 #incorrect word
            elif response == 'a' and location == 0:
                word_value_dict[word] = -1 #incorrect word
            elif response == 'b' and location == 0:
                word_value_dict[word] = 1 #correct word
            else:
                word_value_dict[word] = -1 #invalid value
except FileNotFoundError:
    print(f'File not found for subject: {s} - testTrials.csv')
    continue 

            if word in word_value_dict.keys():
                correct = word_value_dict[word]
            else:
                correct = 0

            print({correct}, file=fout, end='')
except FileNotFoundError:
    print(f'File not found for subject: {s} - studyTrials.csv')

此前尝试的方法 #

尝试直接用row['money']做判断，结果还是全为-1：

if response == 'c' and location == -150 and row['money'] == 1:
    word_value_dict[word] = 1 #correct word
elif response == 'a' and location == 150 and row['money'] == 1:
    word_value_dict[word] = 1 #correct word
elif response == 'c' and location == -150 and row['money'] == 0.01:
    word_value_dict[word] = 1 #correct word 
elif response == 'a' and location == 150 and row['money'] == 0.01:
    word_value_dict[word] = 1 #correct word
elif response == 'c' and location == 0:
    word_value_dict[word] = -1 #incorrect word
elif response == 'a' and location == 0:
    word_value_dict[word] = -1 #incorrect word
elif response == 'b' and location == 0:
    word_value_dict[word] = 1 #correct word
else:
    word_value_dict[word] = -1 #invalid value

#this just outputted all the values as -1 as well. 

尝试把else分支设为None，结果全为None：

else:
    word_value_dict[word] = None #invalid value

#This outputted all the values as None

问题原因及解决方法 #

核心问题 #

1. 缩进错误：代码中if word in word_value_dict.keys():及后续打印逻辑不在循环内部，且位于第一个try块之外，导致循环生成的word_value_dict根本没被使用，打印的correct值逻辑完全错误。
2. 浮点数精度问题：直接用==比较money和1、0.01这类浮点数，可能因为CSV读取时的精度损失导致判断不成立。
3. 输入值格式问题：response可能包含多余空格（比如'c '而非'c'），导致字符串匹配失败。

修正后的代码 #

import math
import pandas as pd

# get correct/incorrect for each word from testTrials.csv
word_value_dict = {}
try:
    df = pd.read_csv(s + 'testTrials.csv')
    # 不需要重复打开文件，pd.read_csv已经读取了内容
    for row_index, row in df.iterrows():
        if pd.isna(row['money']) or row['money'] == 'money':
            continue
        word = row['word']
        money = float(row['money'])
        # 对response做去空格处理，避免格式问题
        response = str(row['testResp.keys_raw']).strip()
        location = float(row['location'])
        print(f"{s} : Row {row_index}: Response='{response}', Location={location}, Money={money}")

        # 用math.isclose处理浮点数比较，避免精度问题
        is_money_1 = math.isclose(money, 1.0, rel_tol=1e-9)
        is_money_001 = math.isclose(money, 0.01, rel_tol=1e-9)
        is_location_neg150 = math.isclose(location, -150.0, rel_tol=1e-9)
        is_location_pos150 = math.isclose(location, 150.0, rel_tol=1e-9)
        is_location_0 = math.isclose(location, 0.0, rel_tol=1e-9)

        # 简化条件判断
        if (response == 'c' and is_location_neg150 and (is_money_1 or is_money_001)) or \
           (response == 'a' and is_location_pos150 and (is_money_1 or is_money_001)) or \
           (response == 'b' and is_location_0):
            word_value_dict[word] = 1
        elif (response in ['a', 'c'] and is_location_0):
            word_value_dict[word] = -1
        else:
            word_value_dict[word] = -1
            print(f"⚠️  Row {row_index}未匹配任何有效条件：Response='{response}', Location={location}, Money={money}")
        
        # 将判断和打印逻辑放到循环内部
        correct = word_value_dict.get(word, 0)
        print(correct, file=fout, end='')
except FileNotFoundError:
    print(f'File not found for subject: {s} - testTrials.csv')
    continue 
except Exception as e:
    print(f'处理subject {s}时出错：{str(e)}')

关键修改点 #

• 修复缩进，将correct值的判断和打印逻辑移到循环内部，确保每个行处理后立即输出结果。
• 使用math.isclose()替代直接==比较浮点数，解决精度问题。
• 对response做strip()处理，去除前后空格，避免字符串匹配失败。
• 简化条件判断逻辑，减少重复代码，同时增加调试输出，方便定位未匹配条件的行。
• 移除了多余的with open语句，因为pd.read_csv已经完成了文件读取。

内容的提问来源于stack exchange，提问作者Annie Cooper